Overview
- Editors:
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Rolf Findeisen
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Institute for Systems Theory and Automatic Control, University of Stuttgart, Stuttgart, Germany
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Frank Allgöwer
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Institute for Systems Theory and Automatic Control, University of Stuttgart, Stuttgart, Germany
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Lorenz T. Biegler
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Chemical Engineering Department, Carnegie Mellon University, Pittsburgh, USA
- Results of the international workshop entitled "Assesmentand Future Directions of Nonlinear Model Predictive Control” (NMPC´05), which was held in Freudenstadt-Lauterbad, Germany on August 26-30, 2005
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Table of contents (53 chapters)
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Robustness, Robust Design, and Uncertainty
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- 1Mark Cannon, Paul Couchman, Basil Kouvaritakis
Pages 255-268
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- Jan M. Maciejowski, Andrea Lecchini Visintini, John Lygeros
Pages 269-281
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- Hong Chen, Xingquan Gao, Hu Wang, Rolf Findeisen
Pages 283-294
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- Lei Xie, Pu Li, GĂĽnter Wozny
Pages 295-304
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- Harvey Arellano-Garcia, Moritz Wendt, Tilman Barz, Guenter Wozny
Pages 305-315
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- D. Limon, T. Alamo, J. M. Bravo, E. F. Camacho, D. R. Ramirez, D. Muñoz de la Peña et al.
Pages 317-326
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- Rafail Gabasov, Faina M. Kirillova, Natalia M. Dmitruk
Pages 327-334
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State Estimation and Output Feedback
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- Angelo Alessandri, Marco Baglietto, Giorgio Battistelli
Pages 347-358
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- John Bagterp Jørgensen, Morten Rode Kristensen, Per Grove Thomsen, Henrik Madsen
Pages 359-366
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Industrial Perspective on NMPC
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- Kelvin Naidoo, John Guiver, Paul Turner, Mike Keenan, Michael Harmse
Pages 383-398
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- RĂĽdiger Franke, Jens Doppelhamer
Pages 399-406
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- Bjarne A. Foss, Tor S. Schei
Pages 407-417
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NMPC and Process Control
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- Jitendra V. Kadam, Wolfgang Marquardt
Pages 419-434
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- José M. Igreja, João M. Lemos, Rui Neves da Silva
Pages 435-441
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- Kenneth R. Muske, Amanda E. Witmer, Randy D. Weinstein
Pages 443-453
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- Peter KĂĽhl, Moritz Diehl, Aleksandra Milewska, Eugeniusz Molga, Hans Georg Bock
Pages 455-464
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- Zoltan K. Nagy, Bernd Mahn, Rüdiger Franke, Frank Allgöwer
Pages 465-472
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- Achim KĂĽpper, Sebastian Engell
Pages 473-483
About this book
Thepastthree decadeshaveseenrapiddevelopmentin the areaofmodelpred- tive control with respect to both theoretical and application aspects. Over these 30 years, model predictive control for linear systems has been widely applied, especially in the area of process control. However, today’s applications often require driving the process over a wide region and close to the boundaries of - erability, while satisfying constraints and achieving near-optimal performance. Consequently, the application of linear control methods does not always lead to satisfactory performance, and here nonlinear methods must be employed. This is one of the reasons why nonlinear model predictive control (NMPC) has - joyed signi?cant attention over the past years,with a number of recent advances on both the theoretical and application frontier. Additionally, the widespread availability and steadily increasing power of today’s computers, as well as the development of specially tailored numerical solution methods for NMPC, bring thepracticalapplicabilityofNMPCwithinreachevenforveryfastsystems.This has led to a series of new, exciting developments, along with new challenges in the area of NMPC.
Reviews
“It is a wide ranging text covering such areas as hybrid systems, constrained control, LPV systems, nonlinear discrete-time systems and many others. … This is a valuable contribution to the subject and is suitable for researchers and engineers involved in all aspects of nonlinear MPC design and implementation.” (ACTC applied control technology consortium, actc-control.com, March, 2016)